Building a Multi-Layer Perceptron in TensorFlow: Introduction to Deep Learning
Learn the basics of deep learning and walk through building an MLP using TensorFlow
Deep learning is a subset of machine learning that focuses on using neural networks to solve complex problems. Let’s learn the basics of deep learning and walk through building a multi-layer perceptron (MLP) using TensorFlow.
What is Deep Learning?
Deep learning is a subset of machine learning that focuses on using neural networks with multiple layers to solve complex problems. The idea behind deep learning is to learn features automatically from the input data rather than relying on human-designed features. Deep learning has achieved impressive results in various applications such as computer vision, natural language processing, and speech recognition.
What is a Multi-Layer Perceptron?
A multi-layer perceptron (MLP) is a type of neural network that consists of multiple layers of neurons, including an input layer, one or more hidden layers, and an output layer. Each neuron in the hidden layers is connected to all the neurons in the previous layer, and each connection has a weight associated with it. MLPs can be used for both…
